/* 
 * This file is part of the UEA Time Series Machine Learning (TSML) toolbox.
 *
 * The UEA TSML toolbox is free software: you can redistribute it and/or 
 * modify it under the terms of the GNU General Public License as published 
 * by the Free Software Foundation, either version 3 of the License, or 
 * (at your option) any later version.
 *
 * The UEA TSML toolbox is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License along
 * with the UEA TSML toolbox. If not, see <https://www.gnu.org/licenses/>.
 */
 
package tsml.classifiers.multivariate;

import tsml.classifiers.legacy.elastic_ensemble.distance_functions.EuclideanDistance_I;
import static utilities.InstanceTools.findMinDistance;
import utilities.generic_storage.Pair;
import weka.core.Instance;
import weka.core.Instances;

/**
 *
 * @author Aaron
 */
public class NN_ED_I extends MultivariateAbstractClassifier{
    
    Instances train;
    EuclideanDistance_I I;
    public NN_ED_I(){
        I = new EuclideanDistance_I();
    }



    @Override
    public void buildClassifier(Instances data) throws Exception {
        testWithFailRelationalInstances(data);
        train = data;
    }
    
    @Override
    public double classifyInstance(Instance instance) throws Exception{
        testWithFailRelationalInstance(instance);
        Pair<Instance, Double> minD = findMinDistance(train, instance, I);
        return minD.var1.classValue();
    }
}
